1. Field of the Invention
The present invention relates to load and stress prediction on aircraft structures, and in particular to fatigue spectra generation for accurately, quickly, and efficiently determining the cyclic stresses that an aircraft will be exposed to during its lifetime.
2. Related Art
An aircraft undergoes numerous stresses during its lifetime. Discrete events of the aircraft, such as air and ground maneuvers, produce numerous external loads that are applied to various parts of the airframe that cause stresses on the airframe. Therefore, due to the numerous types of maneuvers that the aircraft might undergo, the means of predicting the stress accurately for each of the discrete events is extremely important.
Fatigue spectra generation predicts the amount of stress that the aircraft will be subjected to for each event represented in a profile of events that are expected during the life of the aircraft. Current fatigue spectra generation processes rely on regression techniques. In one such example, first a multitude of balanced external load conditions have to be generated. Next, a finite element model utilizes the balanced external load conditions to obtain internal loads. Then, a best fit equation must be derived to relate the internal loads to the external load summations at key control points such as the Wing root, Horizontal root, Vertical root and select fuselage stations for every event in the profile of events that are expected during the life of the aircraft. The external load summations described above are obtained from well known aeroelastic analysis procedures. Since the external loads at key interfaces (wing root, horizontal root, etc.) are available from such an aeroelastic analysis for every event, internal loads for every event can be derived using the regression equation.
However, current regression techniques often produce inaccuracies if the regression fit is `forced` due to the limitations in the availability of the balanced external load conditions. Also, regression techniques are time consuming since they require the generation of a regression equation for every element in the Finite element model for which a fatigue spectrum is required.
Therefore, what is needed is an accurate fatigue spectra generation process which eliminates the demand on generating fully balanced conditions for every event in the profile of events expected during the life of the aircraft. What is further needed is a fast and efficient fatigue spectra generation process which precludes the need to generate a regression equation for every member in the Finite element model of the aircraft.
Whatever the merits of the above mentioned systems and methods, they do not achieve the benefits of the present invention.